Fanconi anaemia is a very rare genetic disease. Due to the small number of patients, it is difficult to conduct clinical trials on it. Scientists from an international team propose using advanced mathematics to collect large amounts and various types of genetic and health data from a limited number of patients.
'Multi-level dynamic modelling is an advanced mathematical and computational approach used in various fields of science and engineering, which allows for analysing and explaining complex patterns,’ explains Professor Carsten Carlberg from the Institute of Animal Reproduction and Food Research at the Polish Academy of Sciences in Olsztyn, one of the co-authors of the publication on the topic published in the journal Frontiers in Genetics.
Fanconi anaemia (FA) occurs in one-in-300,000 people. It is primarily caused by mutations in 22 different genes involved in repairing damaged DNA.
People with Fanconi anaemia often have congenital defects and a high risk of cancer, especially squamous cell carcinoma of the oral cavity. Due to gene mutations and a defect in the DNA repair process, traditional cancer treatment methods such as chemotherapy cannot be used in this disease.
The problem in better understanding Fanconi anaemia is the small number of patients and, consequently, difficulties in conducting clinical trials with their participation. Advanced mathematics comes to the rescue.
Professor Carlberg says that mechanistic molecular modelling is a computational approach that is well suited to the analysis of longitudinal studies of groups of people with a limited number of participants (longitudinal studies allow to observe the same people repeatedly and over many years). These limitations may have various reasons: logistical, financial ones, or because the studied disease, such as Fanconi anaemia, is rare.
In contrast, multi-level dynamic modelling is a special case of mechanistic modelling in which a large amount of data is collected for one person and then used to create models of that person’s cells and tissues. These models are sometimes referred to as 'digital twins'.
'To create and +train+ the model, we use data from healthy and diseased tissue samples from a unique cohort of 750 patients with FA, which was built over 15 years by Professor Eunike Velleuer. On this basis, we develop the characteristic features of squamous cell carcinoma in patients with Fanconi anaemia, which in turn allows us to develop forecasts regarding the probability of developing this cancer,’ says Professor Carlberg.
'This approach may revolutionise the way of clinical treatment of people with Fanconi anaemia,’ adds the leader of the research team, Professor Eunike Velleuer from the University of Düsseldorf (Germany), one of the world's leading Fanconi anaemia experts and the first author of the publication.
The Polish-German team collaborates with researchers from Mexico and the US, who are experts in mechanistic modelling and/or Fanconi anaemia. The consortium’s ultimate goal is to create 'digital twins' of FA patients which can be used to develop personalized treatment routes.
However, using mechanistic modelling and building medical 'digital twins' is by far not restricted to Fanconi anaemia, but can be applied to many investigations such as longitudinal effects of vitamin D supplementation, says Professor Carlberg.
Professor Carsten Carlberg is a world-famous biochemist specializing in research on vitamin D. He is the leader of the scientific group dealing with nutrigenomics at the Institute of Animal Reproduction and Food Research of the Polish Academy of Sciences in Olsztyn.
Find out more about the team's research on the website. (PAP)
PAP - Science in Poland, Agnieszka Libudzka
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